搜索资源列表
主成分分析法
- 主成分分析发doashdasnlkasnlkasnd(principal component analysis)
《MATLAB统计分析与应用3》
- 距离判别分析法、贝叶斯判别分析法;主成分分析matlab函数等(Distance discriminant analysis, Bias discriminant analysis, principal component analysis, matlab function, etc.)
spca
- 本程序实现稀疏主成分分析,相关方法在 H. Zou, T. Hastie, and R. Tibshirani的Sparse principal component analysis中有详细介绍(For SPCA, the method introduced in "Sparse principal component analysis" by H. Zou, T. Hastie, and R. Tibshirani)
主成分分析
- 该代码是主成分分析法的matlab实现,简单方便使用(The code is the principal component analysis of Matlab implementation, simple and convenient to use)
主成分分析法
- 内涵主成分分析法的PPT,案例和matlab编写的代码。(Connotation of principal component analysis of PPT, case and matlab prepared by the code.)
PCA
- 主成分分析matlab代码,Cwprint为主函数;(PCA based on matlab. very useful.)
m03
- 主成分分析发实例,数据在mat文件中,运行前需要将其调入内存,主要用于光谱分析。(Example of principal component analysis)
PCA
- 该程序可以实现数据的主成分提取,以及相关系数矩阵,得分矩阵,还有T^2统计量,可视化效果好。(The program can achieve the main component extraction of data, as well as correlation coefficient matrix, scoring matrix, as well as T^2 statistics, visual effect is good.)
独立成分分析ICA
- 完整的独立成分分析的示例程序,有四幅图像,生动详细(Complete independent component analysis of the sample program, there are four images, vivid detail)
主成分分析法Nicolas_PCA
- 将多个变量通过线性变换以选出较少个数重要变量的一种多元统计分析方法(A multivariate statistical analysis method in which multiple variables are selected by linear transformation to select fewer significant variables)
ImageFusion_PCA
- 在GDAL库下,采用主成分变换实现多光谱影像与全色高分辨影像的融合。(Under the GDAL library, the principal component transformation is used to fuse multispectral images with panchromatic high resolution images.)
zhuchengfen
- 改进的主成分分析法,可算出指标的相对贡献值(The relative contribution value of the index can be calculated by the improved principal component analysis)
pca
- 通过主成分分析可以对混合物量测矩阵进行svd分解,截取特征值大的变量,可以滤掉一些无关信息,使计算量更小(Through the principal component analysis of the mixture can be measured matrix svd decomposition, interception of large eigenvalues of variables, you can filter out some irrelevant information, so
pcr
- 主成分回归是一种多元回归分析方法,旨在解决自变量间存在多重线性问题(Principal component regression is a multivariate regression analysis method designed to solve the existence of multiple linear problems between independent variables)
PCA
- 高光谱遥感与传统的单波段、多光谱数据相比,波段量大量增加、波段宽度极大降低,对地面目标的光谱特性的测度更加细致,然而波段的增多必然导致数据量急剧增加、计算量增大、信息冗余增加以及统计参数的估计偏差增大。因此,对高光谱数据进行降维处理具有重要意义。一方面,降维能够使图像远离噪声,提高图像数据质量;另一方面,能够去除图像中的无价值波段,减少波段数,从而降低计算量,提高运算效率。主成分分析是常用的高光谱数据降维处理方法之一。(Compared with the single band, hypersp
主成分和因子分析
- 主成分分析是多元统计分析中用来分析数据的一种方法,它是用一种较少数量的特征对样本进行描述以达到降低特征空间维数的方法(Principal component analysis is a method of data used in multivariate statistical analysis, it is describing the samples with characteristics of a small number of methods to reduce the dimens
主成分分析法的原理应用及计算步骤
- PCA算法详细介绍:word版可以打印,值得与君共欣赏(PCA:Principal Component Analysis)
第12章 主成分分析
- 主成分分析,主要是一些案例的源文件。可以参考MATLAB的40个数值分析案例。分为三个,一个是数值分析,一个是基础操作,最后一个是演示。(principal component analysis)
436805212DPCA
- 有关图像的二维主成分分析,详细解释,简单易懂,有益于学习(The two dimensional principal component analysis of the image is explained in detail. It is easy to understand and is beneficial to learning.)
PCA分析源代码
- PCA主成分分析源代码,PCA是用于降维是经典方法,现在仍有很多人用主成分分析方法进行降维,降低算法复杂度。(PCA is the source code of principal component analysis. PCA is a classical method for dimensionality reduction. Many people still use principal component analysis to reduce dimension and reduce a